Linguistic linked data : representation, generation and applications /

This is the first monograph on the emerging area of linguistic linked data. Presenting a combination of background information on linguistic linked data and concrete implementation advice, it introduces and discusses the main benefits of applying linked data (LD) principles to the representation and...

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Hlavní autoři: Cimiano, Philipp (Autor), Chiarcos, Christian (Autor), McCrae, John (Autor), Gracia del Río, Jorge (Autor)
Typ dokumentu: Kniha
Jazyk:Angličtina
Vydáno: Cham : Springer, [2020]
Témata:
On-line přístup:Elektronická verze přístupná pouze pro studenty a pracovníky MU
Příbuzné jednotky:Tištěná verze:: Linguistic Linked Data : representation, generation and applications
Popis
Shrnutí:This is the first monograph on the emerging area of linguistic linked data. Presenting a combination of background information on linguistic linked data and concrete implementation advice, it introduces and discusses the main benefits of applying linked data (LD) principles to the representation and publication of linguistic resources, arguing that LD does not look at a single resource in isolation but seeks to create a large network of resources that can be used together and uniformly, and so making more of the single resource. The book describes how the LD principles can be applied to modelling language resources. Given its scope, the book is relevant for researchers and graduate students interested in topics at the crossroads of natural language processing / computational linguistics and the Semantic Web / linked dat a. It appeals to Semantic Web experts who are not proficient in applying the Semantic Web and LD principles to linguistic data, as well as to computational linguists who are used to working with lexical and linguistic resources wanting to learn about a new paradigm for modelling, publishing and exploiting linguistic resources.
Fyzický popis:1 online zdroj (xvi, 286 stran) : ilustrace
Bibliografie:Obsahuje bibliografické odkazy
ISBN:978-3-030-30225-2